Skip to main content Accessibility help
×
Hostname: page-component-84b7d79bbc-tsvsl Total loading time: 0 Render date: 2024-07-26T01:19:16.608Z Has data issue: false hasContentIssue false

23 - Why are circuit lower bounds so difficult?

from PART THREE - ADVANCED TOPICS

Published online by Cambridge University Press:  05 June 2012

Sanjeev Arora
Affiliation:
Princeton University, New Jersey
Boaz Barak
Affiliation:
Princeton University, New Jersey
Get access

Summary

The main hurdle in proving a lower bound is the existence of an algorithm.

–Steven Rudich

Why have we not been able to prove strong lower bounds for general circuits? Despite the dramatic success in proving lower bounds on restricted circuit classes as described in Chapter 14, we seem utterly at a loss when it comes to showing limitations of general Boolean circuits.

In 1994 Razborov and Rudich [RR94] described what they view as the main technical limitation of current approaches for proving circuit lower bounds. They defined a notion of “natural mathematical proofs” for a circuit lower bound. They pointed out that current lower bound arguments involve such mathematical proofs, and showed that obtaining strong lower bound with such proof techniques would violate a stronger form of the PNP conjecture–specifically, the conjecture that strong one-way functions exist that cannot be inverted by algorithms running in subexponential time. Since current evidence suggests that such strong one-way functions do exist (factoring integers, discrete log, etc., as described in Chapter 9), we conclude that current techniques are inherently incapable of proving strong lower bounds on general circuits.

The Razborov-Rudich result may be viewed as a modern analog of the 1970s results on the limits of diagonalization (see Chapter 3). What is particularly striking is that computational complexity (namely, the existence of strong one-way functions) is used here to shed light on a metamathematical question about computational complexity: “Why have we been unable to prove PNP?”

Type
Chapter
Information
Computational Complexity
A Modern Approach
, pp. 498 - 507
Publisher: Cambridge University Press
Print publication year: 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×